A Kinect based gesture recognition algorithm using GMM and HMM

摘要

Gesture recognition is a quite promising field in robotics and many Human-Computer Interaction (HCI) related areas. This research uses Microsoft® Kinect to capture the 3D position data of joints, and uses Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) to model full-body gestures. We propose a gesture recognition algorithm to segment gestures from real-time data flow, and finally achieved to recognize predefined full-body gestures in real-time. This proposed method gives a high recognition rate of 94.36%, indicating the capability of the new method.